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Your search keyword '"Kwon, Soon-Bark"' showing total 34 results
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34 results on '"Kwon, Soon-Bark"'

33. Inhalation cancer risk from PM10in the metropolitan subway stations in Korea

Author

Roy, Debananda, Seo, Yong-Chil, Namgung, Hyeong-Gyu, and Kwon, Soon-Bark

Abstract

Although subways have many advantages as a transport system, passengers may be exposed to indoor air pollution. In such cases, the dominant risk factors are associated with particulate matter (PM) bound metals and polycyclic aromatic hydrocarbons (PAHs). In this study, inhalation cancer risks (ICR) were assessed at Seoul metro subway stations (SMS), South Korea, in 2014–2015.

Published
2019
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34. Predicting PM 10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN).

Author

Park S, Kim M, Kim M, Namgung HG, Kim KT, Cho KH, and Kwon SB

Abstract

The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Published
2018
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